Abstract
Objective: Cardiac ultrasound imaging systems are limited in the noninvasive quantification of valvular regurgitation due to indirect measurements and inaccurate hemodynamic assumptions. We recently demonstrated that the principle of integration of backscattered acoustic Doppler power times velocity can be used for flow quantification in valvular regurgitation directly at the vena contracta of a regurgitant flow jet. We now aimed to accomplish implementation of automated Doppler power flow analysis software on a standard cardiac ultrasound system utilizing novel matrix-array transducer technology with detailed description of system requirements, components and software contributing to the system. Methods: This system based on a 3.5 MHz, matrix-array cardiac ultrasound scanner (Sonos 5500, Philips Medical Systems) was validated by means of comprehensive experimental signal generator trials, in vitro flow phantom trials and in vivo testing in 48 patients with mitral regurgitation of different severity and etiology using magnetic resonance imaging (MRI) for reference. Results: All measurements displayed good correlation to the reference values, indicating successful implementation of automated Doppler power flow analysis on a matrix-array ultrasound imaging system. Systematic underestimation of effective regurgitant orifice areas >0.65 cm2 and volumes >40 ml was found due to currently limited Doppler beam width that could be readily overcome by the use of new generation 2D matrix-array technology. Conclusion: Automated flow quantification in valvular heart disease based on backscattered Doppler power can be fully implemented on board a routinely used matrix-array ultrasound imaging systems. Such automated Doppler power flow analysis of valvular regurgitant flow directly, noninvasively, and user independent overcomes the practical limitations of current techniques.
| Originalsprache | Englisch |
|---|---|
| Zeitschrift | International Journal of Cardiovascular Imaging |
| Jahrgang | 24 |
| Ausgabenummer | 5 |
| Seiten (von - bis) | 463-477 |
| Seitenumfang | 15 |
| ISSN | 1569-5794 |
| DOIs | |
| Publikationsstatus | Veröffentlicht - 01.06.2008 |
Fördermittel
Acknowledgements T. Buck was supported by grants Bu1097/ 2-1 and Bu 1097/2-2 from the Deutsche Forschungsgemeinschaft, Bonn, Germany. S.M. Hwang was a student of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology in the years 1999 till 2002. The work was supported in part by NIH grants R01 HL38176, HL53702, and K24 HL67434 of the National Institutes of Health, Bethesda, Maryland to R.A. Levine.
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